Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India.

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.

Hydrological tracers, the herbicide metazachlor and its transformation products in a retention pond during transient flow conditions.

Since decades, surface water bodies have been exposed to pesticides from agriculture. In many places, retention systems are regarded as an important mitigation strategy to lower pesticide pollution. Hence, the processes governing the transport of pesticides in and through a retention system have to be understood to achieve sufficient pesticide attenuation. In this study, the temporal dynamics of metazachlor and its transformation products metazachlor-oxalic acid (OA) and -sulphonic acid (ESA) were observed in an agricultural retention pond and hydrologic tracers helped to understand system-inherent processes. Pesticide measurements were carried out for 80 days after their application during transient flow conditions. During a short-term (3 days) experiment, the tracers bromide, uranine and sulphorhodamine B were used to determine hydraulic conditions, residence times and sorption potential. A long-term experiment with sodium naphthionate (2 months) and isotopes (12 months) provided information about inputs via interflow and surface-groundwater interactions. During transient conditions, high concentration pulses of up to 35 µg L-1 metazachlor, 14.7 µg L-1 OA and 22.5 µg L-1 ESA were quantified that enduringly raised solute concentrations in the pond. Mean residence time in the system accounted for approximately 4 h showing first tracer breakthrough after 5 min and last tracer concentrations 72 h after injection. While input via interflow was confirmed, no evidence for surface-groundwater interaction was found. Different tracers illustrated potentials for sorption and photolytic degradation inside the system. This study shows that high-resolution sampling is essential to obtain robust results about retention efficiency and that hydrological tracers may be used to determine the governing processes.